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Applied Scientist II - ML at Microsoft
Redmond, Washington, United States -
Full Time

Start Date

Immediate

Expiry Date

13 Jan, 26

Salary

0.0

Posted On

15 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Machine Learning, Data Science, Predictive Analytics, Causal Inference, Collaboration, Opportunity Analysis, Hypothesis Generation, Forecasting

Industry

Software Development

Description
The Insights, Data Engineering & Analytics team (IDEAS), is a central data science team for M365 engineering and marketing. As one of the largest data science groups at Microsoft, our team plays a key role in providing data and analytics for M365 and owns the end to end ML and decision sciences charter. By joining our team, you will be at the heart of data, insights, machine learning, AI, and technology, lighting up actionable insights that drive key business decisions for the entire M365 organization. As a Applied Scientist II - ML in IDEAs team, you will be bringing relevant data into a central systems to create the single version of truth and perform opportunity analysis and hypothesis generation for stages throughout the end-to-end customer lifecycle. This opportunity will allow you to gain experiencein designing, prototyping, implementing and testing descriptive, predictive analytics, forecasting, causal inference models and also thrive in a team environment that values cross team collaboration and building on the success of others. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Responsibilities
As an Applied Scientist II - ML, you will bring relevant data into central systems to create a single version of truth and perform opportunity analysis. You will design, prototype, implement, and test various analytics models throughout the customer lifecycle.